Various abbreviations that appear in the specification and/or in the drawing figures are defined as follows:
BSbase stationCDMAcode division multiple accessDLdownlink (BS to MS)EUTRANevolved universal terrestrial radio access networkFDMAfrequency division multiple accessLTElong term evolutionMIMOmultiple-input, multiple-outputMFmatched filterMLmaximum likelihoodMMSEminimum mean squared errorMSmobile stationMUmultiuserSDMAspatial division multiple accessTDMAtime division multiple accessWiMAXworldwide interoperability for microwave access (IEEE 802.16)
MIMO takes advantage of multiplexing to increase wireless bandwidth and range. MIMO algorithms send information out over two or more antennas and the information is received via multiple antennas. While in a conventional sense such multiplexing would cause interference, MIMO uses the additional pathways to transmit more information and then recombines the signal at the receiver. A MIMO system provides a significant capacity gain over conventional single antenna systems, in addition to more reliable communication.
Various publications that may be of interest herein include:
W. Ajib and D. Hoccoun, “An overview of scheduling algorithms in MIMO-based fourth-generation wireless systems,” IEEE Network, September/October 2005, incorporated by reference;
R. W. Heath Jr., M. Airy, and A. J. Paulraj, “Multiuser diversity for MIMO wireless systems with linear receivers” Conference Record of the Thirty-Fifth Asilomar Conference on Signals, Systems and Computers, 4-7 November 2001, Vol. 2, pp. 1194-1199, incorporated by reference;
B. Bandemer, S. Visuri, “Capacity-Based Uplink Scheduling Using Long-Term Channel Knowledge,” ICC '07. IEEE International Conference on Communications, 24-28 Jun. 2007, pp. 785-790, incorporated by reference; and
H. W. Kuhn, “The Hungarian Method for the assignment problem,” Naval Research Logistic Quarterly, 2:83-97, 1955, and also incorporated by reference.
Reference may also be made to C. Wang, R. Murch, “Adaptive Downlink Multi-User MIMO Wireless Systems for Correlated Channels with Imperfect CSI”, III Transactions on Wireless Communications, Vol. 5, No. 9, pp. 2455-2446, September 2006, and incorporated by reference. This publication discusses in Section D an adaptive MU-MIMO grouping algorithm, where a number of users in a group may be constrained to be two.
In general, a MU-MIMO uplink (multipoint-to-point) system is characterized by K users with nt antennas each communicating to a base station or to a receiver with nr receive antennas. Since each user faces a different channel condition in different time/frequency/code (TFC) slots it is possible to improve the overall system capacity by MU scheduling. Provided that spatial separation of the users is sufficient, it is possible to have two or more users assigned to the same time-frequency-code slot (i.e., to also use SDMA or Spatial Division Multiple Access). This technique attempts to increase the system capacity by intelligently allocating the channel to different subgroups of users. In downlink (point-to-multipoint) channels, the problem is different in that there is one source transmitting to K users. A general introduction to this topic can be found in W. Ajib and D. Hoccoun, “An overview of scheduling algorithms in MIMO-based fourth-generation wireless systems,” IEEE Network, September/October 2005. Among the most popular MU scheduling schemes are opportunistic scheduling and best subset selection. All scheduling schemes are confronted with a fairness issue that may force the sacrifice of overall network optimality in order to guarantee all users with a minimum service requirement.